AMA, Agricultural Mechanization in Asia, Africa and Latin America (AMA) (issn: 00845841) is a peer reviewed journal first published online after indexing scopus in 1982. AMA is published by Farm Machinery Industrial Research Corp and Shin-Norinsha Co. AMA publishes every subjects of general engineering and agricultural engineering. Azerbaijan Medical Journal Gongcheng Kexue Yu Jishu/Advanced Engineering Science Zhonghua er bi yan hou tou jing wai ke za zhi = Chinese journal of otorhinolaryngology head and neck surgery Interventional Pulmonology Kongzhi yu Juece/Control and Decision Zhenkong Kexue yu Jishu Xuebao/Journal of Vacuum Science and Technology Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering) Zhonghua yi shi za zhi (Beijing, China : 1980)
AMA, Agricultural Mechanization in Asia, Africa and Latin America (ISSN: 00845841) is a peer-reviewed journal. The journal covers Agricultural and Biological Sciences and all sort of engineering topic. the journal's scopes are in the following fields but not limited to:
Identification of appropriate method of mechanical weed control and inter-culture suitable crop row spacing are the important researchable areas in pearl millet agronomy. Considering this research gap, field experiment entitled “Weed dynamics, crop productivity and profitability of pearl millet as influenced by mechanized weed control under semi-arid agro-ecology of India” was undertaken with the aim of finding out the effect of experimentation on weed dynamics (weed flora distribution, weed density, weed control efficiency and weed index), crop productivity and profitability parameters (gross returns, cost of cultivation, net returns and benefit: cost (B:C) of pearl millet. The field experiment was carried out in Kharif, 2017 at Regional Research Station, Bawal, Rewari of Chaudhary Charan Singh Haryana Agriculture University (CCSHAU), Hisar. A combination of twelve treatments (manual weeding by kasola and wheel hand hoe however; mechanized weeding by tractor and power weeder) were allocated in randomized block design and replicated thrice. Dominant weed flora in the study were Cyperus rotundus, Trianthema portulacastrum, Digera arvensis whose relative weed density was 42% & 46%, 26% & 22% and 17% & 15% at 20 days after sowing (DAS) and at maturity stage, respectively. Treatment T8 (sowing at 60 cm row spacing and two inter-culture with power weeder) has resulted in lowest weed density and weed dry matter at 20 DAS while, T1 (sowing at 45 cm row spacing and two interculture with kasola) has resulted in lowest weed density, weed dry matter (2.66 & 3.41 g/m2) and weed control efficiency (92.5 & 89.1%) at 40 DAS and at maturity respectively T1 also resulted in lowest weed index (3.09%), higher crop productivity (29.43, 68.50 and 97.93 q/ha of grain, stover and biological yield, respectively) and high value of cost of cultivation and gross returns. However, T7 (sowing at 60 cm row spacing and two interculture with tractor) noted with at par productivity but higher net returns (Rs/ha, 23777.7) and higher B: C ratio (1.80) than T1.
Study was carried out in Haryana state to assess the adoption of inland fishery farming practices and constraints faced by fishery farmers of Haryana state. The findings revealed that majority of fish farmers (58.67%) possessed large size ponds and all were perennial in nature but 52.00 percent of them were using leased village ponds. The overall adoption for fish farming technology was low (56.00%). While the practices such as recommended species, watering of ponds and stocking fish seed, recommended fish seed rate or fingerlings application, proper harvesting period and pond site management practices were fully adopted by farmers whereas, least adopted practices included control of aquatic weeds, ploughing of pond, disease control measure and application of recommended manures and fertilizers. However, very serious constraints in fish farming were viz. lack of knowledge of field functionaries for post-harvest management practices, lack of knowledge of modern storage structures, non-availability of fish feed and seed at proper time in villages, lack of remunerative fish MSP policy, wide price fluctuations, high price of fish seed and no cold storages at villages. Both technological empowerment as well as remunerative and assured markets is very crucial for sustainability and profitability of this farming enterprise.
Pearl grass is a plant that can be used as a medicine for various diseases, such as cancer, hepatitis, diabetes, wounds, eye pain, fever, and stomach. Pearl grass contains several chemical compounds, and of them are ursolic acid and oleanolic acid. Using chicken manure and arbuscular mycorrhizal has the potential to be a cultivation technology to determine ursolic acid levels in the pearl grass. The research was carried out in Jumantonso, Karanganyar, Central Java. The research was conducted from December 2019-February 2020. The study used a completely randomized design (CRD) with 2 factors. The first factor is chicken manure at a dosage of 0, 7.5, 15 tons/ha. The second factor was arbuscular mycorrhizal at the dosage of 0, 5, 10, 15 g/plant. The treatment combination consisted of 5 replications. The variables observed were plant height, number of branches, plant crown diameter, root length, plant root weight, fresh plant weight, plant dry weight, and ursolic acid content. The results showed that the application of chicken manure 7.5 tons/ha was able to affect all parameters except for the length and weight of pearl grassroots. The various doses of arbuscular mycorrhizal did not affect all growth and yield parameters of pearl grass. Application of chicken manure and arbuscular mycorrhizae resulted in high levels of ursolic acid in most treatment doses. The application of chicken manure and arbuscular mycorrhizae increased the growth and yield of pearl grass but did not provide interaction on the growth and yield of pearl grass.
It is expected that environmental changes influence the growth and development of crop, and with this hypothesis, a field experiment was laid to investigate the impact of different dates of transplanting on various genotypes of basmati rice. Three genotypes of basmati rice i.e. CSR 30, Pusa Basmati (PB) 1121 and Haryana Basmati (HB) 2 were sown with three transplanting dates (June 25, July 10 and July 25) in the kharif season of 2015 and 2016 using. The experiment was designed in a split-plot layout with four replications, where dates of transplanting were allocated to the main plots and the genotypes to the subplots. The ANOVA table showed that the main effects of the dates of transplanting and the genotype are significant for nearly all the assessed characters. Significant interaction between the date of transplantation and the genotype were observed for number of effective tillers (NET), harvest index (HI) and straw yield (SY). The grain yield (GY) on first date of transplanting (25th June) showed significant incrememt by ~2.5 and ~17% relative to the second (10th July) and third date of transplanting (25th July), respectively. The findings of this study revealed that early transplanting enhanced positive effects on assessed characters of basmati rice. Further, correlation study has exhibited the positive and significant correlation (p≤0.05) of GY with NET, number of grains per panicle (NGPP), panicle length (PL), 1000-grain weight (GW) and HI.
The present investigation deals with the use of Coefficient of Variation (CV), Cuddy-Della Valle index (CDVI), Coppock’s instability index (CII), to determine the instability in the wheat production in major producing states in India. Time series data for the period (1960–1961 to 2018–2019) on area, production, yield and MSP of wheat have been used in this study. Time series data was divided into six decades of 10-year interval to measure the instability in area, production and yield of selected crops into different periods. Annual growth rate of area, production and productivity of wheat crop in India and major wheat growing states were also observed by fitting to the time-series data in linear function.